Tflearn: TypeError: Cannot cast ufunc subtract output from dtype('float64') to dtype('uint8') with casting rule 'same_kind'

[andrfgs]

I don't seem to be able to use TFLearn at all. Whenever I try to run it, Thread 3 in Python crashes, showing this error.

I installed TensorFlow and TFLearn a day ago and I was trying to test this tutorial code: https://medium.com/@ageitgey/machine-learning-is-fun-part-3-deep-learning-and-convolutional-neural-networks-f40359318721

Using:
Windows 10, Python 3.6
Anaconda 4.4.10
TensorFlow 1.5
TFLearn 0.32

Full console log:
C:\ProgramData\Anaconda3\lib\site-packages\h5py__init__.py:34: FutureWarning: Conversion of the second argument of issubdtype from float to np.floating is deprecated. In future, it will be treated as np.float64 == np.dtype(float).type.
from ._conv import register_converters as _register_converters
curses is not supported on this machine (please install/reinstall curses for an optimal experience)
WARNING:tensorflow:From C:\ProgramData\Anaconda3\lib\site-packages\tflearn\initializations.py:119: UniformUnitScaling.__init__ (from tensorflow.python.ops.init_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.initializers.variance_scaling instead with distribution=uniform to get equivalent behavior.
WARNING:tensorflow:From C:\ProgramData\Anaconda3\lib\site-packages\tflearn\objectives.py:66: calling reduce_sum (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.
Instructions for updating:
keep_dims is deprecated, use keepdims instead

2018-02-15 06:22:15.563652: I C:\tf_jenkins\workspace\rel-win\M\windows\PY\36\tensorflow\core\platform\cpu_feature_guard.cc:137] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2

Run id: fire-classifier

Log directory: /tmp/tflearn_logs/

Preprocessing... Calculating mean over all dataset (this may take long)...

Mean: 99.04967060701352 (To avoid repetitive computation, add it to argument 'mean' of add_featurewise_zero_center)

Preprocessing... Calculating std over all dataset (this may take long)...

STD: 62.02319644890393 (To avoid repetitive computation, add it to argument 'std' of add_featurewise_stdnorm)

Training samples: 583

Validation samples: 0

Exception in thread Thread-3:
Traceback (most recent call last):
File "C:\ProgramData\Anaconda3\lib\threading.py", line 916, in _bootstrap_inner
self.run()
File "C:\ProgramData\Anaconda3\lib\threading.py", line 864, in run
self._target(self._args, *self._kwargs)
File "C:\ProgramData\Anaconda3\lib\site-packages\tflearn\data_flow.py", line 195, in fill_feed_dict_queue
data[k] = self.dprep_dict[k].apply(data[k])
File "C:\ProgramData\Anaconda3\lib\site-packages\tflearn\data_preprocessing.py", line 46, in apply
batch = m(batch)
File "C:\ProgramData\Anaconda3\lib\site-packages\tflearn\data_preprocessing.py", line 216, in _featurewise_zero_center
batch[i] -= self.global_mean.value
TypeError: Cannot cast ufunc subtract output from dtype('float64') to dtype('uint8') with casting rule 'same_kind'

[diegoxfx]

Same problem

---

TypeError Traceback (most recent call last)
in ()
----> 1 S = p.predict('./imagenes/jumbo_roja/jumbo_roja6.jpg')

in predict(self, image)
41 im = (np.array(im))
42 # Predict
---> 43 prediction = self.model.predict(im)
44 return prediction
45

~/anaconda3/lib/python3.6/site-packages/tflearn/models/dnn.py in predict(self, X)
255 """
256 feed_dict = feed_dict_builder(X, None, self.inputs, None)
--> 257 return self.predictor.predict(feed_dict)
258
259 def predict_label(self, X):

~/anaconda3/lib/python3.6/site-packages/tflearn/helpers/evaluator.py in predict(self, feed_dict)
61 if len(dprep_dict) > 0:
62 for k in dprep_dict:
---> 63 feed_dict[k] = dprep_dict[k].apply(feed_dict[k])
64
65 # Prediction for each tensor

~/anaconda3/lib/python3.6/site-packages/tflearn/data_preprocessing.py in apply(self, batch)
44 batch = m(batch, *self.args[i])
45 else:
---> 46 batch = m(batch)
47 return batch
48

~/anaconda3/lib/python3.6/site-packages/tflearn/data_preprocessing.py in _featurewise_zero_center(self, batch)
214 def _featurewise_zero_center(self, batch):
215 for i in range(len(batch)):
--> 216 batch[i] -= self.global_mean.value
217 return batch
218

TypeError: ufunc 'subtract' output (typecode 'O') could not be coerced to provided output parameter (typecode 'B') according to the casting rule ''same_kind''

[diegoxfx]

Now I get this error

TypeError: ufunc 'subtract' output (typecode 'O') could not be coerced to provided output parameter (typecode 'd') according to the casting rule ''same_kind''

[eshwarkamal]

https://techoverflow.net/2019/05/22/how-to-fix-numpy-typeerror-cannot-cast-ufunc-subtract-output-from-dtypefloat64-to-dtypeint64-with-casting-rule-same_kind/

use this link to solve... it works for me.

[andrfgs]

This has been solved by an update. Closing the issue.

[mjshafizadeh]

https://techoverflow.net/2019/05/22/how-to-fix-numpy-typeerror-cannot-cast-ufunc-subtract-output-from-dtypefloat64-to-dtypeint64-with-casting-rule-same_kind/

use this link to solve... it works for me.

So good,tnX!!!